Autonomous driving paper index
Agentic AI as a System within Systems: A Process Model of Organizational Embedding
One-line summary
Drawing on conceptual theorizing grounded in qualitative research, practitioner insight, and established organizational theory, we propose a four-stage process model of agentic AI embedding and theorize the mechanisms driving transitions across stages.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
As organizations increasingly deploy agentic artificial intelligence (AI) systems capable of autonomous action, existing research continues to conceptualize AI primarily as a tool or decision aid. This framing limits the theoretical understanding of how agentic AI becomes organizationally embedded over time. To address this gap, this paper develops a process theory explaining how agentic AI evolves from a peripheral support tool into an organizationally embedded actor within socio-technical systems. Drawing on conceptual theorizing grounded in qualitative research, practitioner insight, and established organizational theory, we propose a four-stage process model of agentic AI embedding and theorize the mechanisms driving transitions across stages. The study advances a process-oriented understanding of AI-driven organizational transformation by shifting attention from outcomes to organizational embedding. For practitioners, the model provides a diagnostic lens for anticipating how roles, authority, and governance must evolve as AI systems become increasingly agentic.
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